Silicon Valley’s title as the epicenter for startups is no joking matter, and this data visualization created by Business Insider makes the seemingly mystical land of growing innovation more tangible than ever. As they say, seeing is believing, and that’s essentially the core of what’s most effective in this data visualization project that examines the growth of start-ups in not only San Francisco, but in New York and Austin, as well. The visualizations of all three cities are time lapses from 2005-2014, and through the passage of time, the viewer can see where venture funding, dedicated to fostering growth within these start-up companies, is going.
San Francisco’s growth is particularly mesmerizing, as it captures the more recent explosion (2009-2014) of start-up funding and essentially squashes the sizes of the other two cities represented, New York and Austin. The viewer can see that, while both cities definitely have a startup presence, San Francisco’s is much greater and spread out. It’s also interesting to see how New York start-ups are more keen on the “hip” areas of New York, such as Soho and Flatiron, as opposed to the more traditional Midtown. (If you don’t believe me that Soho is one of the coolest spots in NYC, check out this Instagram account).
And lastly, sweet ol’ Austin-just barely keeping up in terms of funding. Looking at Austin’s map, it’s made clear to the viewer that they haven’t received nearly as much start-up funding in as many places as both San Francisco and New York have, but after watching the time-lapse it’s clear that it’s been a relatively steady growth. Contrastingly, New York and, even more so, San Francisco have a recent accelerating growth in start-up funds within their cities.
This visualization is effective for a couple of reasons:
As cool as the visualization is, it definitely comes with it’s disadvantages, disadvantages that could be accounted for in more traditional forms of journalism. In traditional journalism, people are able to understand why, and this is approximately the downfall rooted within data visualization. Nieman Lab talks about the appeal of explanatory journalism, noting that “the complicated how-and-why questions are what we need to understand.” It’s one thing for journalism to tell us what’s happening, it’s another (and arguably more valuable) for it to connect the dots and contextualize information. It’s really hard for data visualization to completely explain to the reader why something is happening, because the more complex the visualization, the more confusing it gets. The more confusing the visualization gets, and suddenly, it loses the advantage it has, that being the ability to effectively conveying information because of simple and engaging imagery.
This particular data visualization lacks a lot of why, which is why it’s not entirely effective. It tells the viewer three simple things 1) where the venture capital funding of start-ups is going 2) when it’s being given and 3) what it looks like in relation to two other cities. But a big downfall, is that it doesn’t explain what start-ups are being benefitted or how much money is going to them. Even more disconnecting, the dots don’t show, relatively, where certain start-ups are getting more funding than others. It’s not like the bigger the bubble on the map, the more funding given to that particular start-up. It simply shows where funding is given and at what period of time. Even the creator of the data visualization maps, Karnik, says this particular visualization isn’t totally comprehensive. He says, “Cities have very different histories and social dynamics that can either foster or stifle entrepreneurship” and notes he “would like to look at population growth and development versus the rate of venture funding to gain further insights.” Maybe this would give the reader a bit more understanding of why certain places are experiencing more growth than others, but even still, words and contextual explanation are things traditional journalism could give information like this, and it’s something data visualization can’t.